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Full Publication Information: http://dx.doi.org/10.1016/j.brainres.2016.04.006 Cite as: Kennefick, M., Maslovat, D., Chua, R., & Carlsen, A. N. (2016). Corticospinal excitability is reduced in a simple reaction time task requiring complex timing. Brain Research, 1642, 319-326. DOI: 10.1016/j.brainres.2016.04.006.
© Copyright 2016 by Dana Maslovat & Anthony N. Carlsen All rights reserved. This article or any portion thereof may not be reproduced or used in any manner whatsoever without the express written permission of the publisher except for the use of brief quotations in a review.
Corticospinal excitability is reduced in a simple reaction time task requiring
complex timing
Michael Kenneficka, Dana Maslovatb,c, Romeo Chuac & *Anthony N. Carlsend
aSchool of Health and Exercise Sciences, University of British Columbia, 1147 Research Road, Kelowna, British Columbia, V1V 1V7, Canada bDepartment of Kinesiology, Langara College, 100 W 49th Ave, Vancouver, British Columbia, V5Y 2Z6, Canada
cSchool of Kinesiology, University of British Columbia, 6081 University Blvd, Vancouver, British Columbia, V6T 1Z1, Canada dSchool of Human Kinetics, University of Ottawa, 125 University Private, Ottawa, Ontario, K1N 6N5, Canada
*Corresponding Author: Email - tony.carlsen@uottawa.ca, tony.carlsen@gmail.com
Received November 4, 2015; Received in revised form March 22, 2016; Accepted April 4, 2016
Abstract
Increasing the complexity of a movement has been shown to result in longer simple reaction time (RT), which
has been attributed to sequencing or timing requirements following the go-signal. However, RT differences may
also be due to differences in corticospinal excitability (CE) as previous studies have found an enhanced excitatory
state of corticospinal neurons in complex tasks. Transcranial magnetic stimulation (TMS) was used in the present
study to probe the excitability of the motor pathway during the simple RT interval for single (simple) versus
multiple (complex) key press responses. Premotor RT data indicated that participants responded significantly (p <
.001) faster in the simple task compared to the complex task, confirming response complexity was manipulated
appropriately. Analysis of the CE data indicated that motor evoked potential (MEP) amplitudes increased with time
following the go-signal in both conditions and that MEP amplitudes in the simple task were significantly larger than
those in the complex task when evoked within 75 ms of movement onset (p = .009). These findings suggest that
the rate of increase for initiation-related neural activation is reduced for complex as compared to simple
movements, which may partially explain differences in RT.
Keywords: Neural activation, Response complexity, Transcranial magnetic stimulation
1. Introduction
The effects of response complexity on the time taken
to react to a stimulus has a long history of research, with
the common finding that an increase in number of
response elements leads to a longer reaction time (RT).
Many explanations have been offered for this response
complexity effect such as an increased amount of time
required to program and retrieve the response from
memory (Henry and Rogers, 1960), or an increase in the
number of processes occurring after the presentation of
the imperative go-signal, such as sequencing or timing
(Klapp, 1995; Maslovat et al., 2014). More recent studies
have suggested that complexity dependent RT differences
may instead relate to levels of neural activation. Models of
neural activation have suggested that motor preparation
can be envisioned as increasing the activation state of
neural networks to a level that is held below the threshold
for initiation (Hanes and Schall, 1996; Wickens et al., 1994).
Reaction time is thus indicative of the time required to
increase neural activation from this preparatory state to a
level beyond threshold. Thus differences in RT can be
attributed to different rates of activation accumulation
(Carpenter and Williams, 1995; Hanes and Schall, 1996),
differences in threshold levels (Nazir and Jacobs, 1991), or
Full Publication Information: http://dx.doi.org/10.1016/j.brainres.2016.04.006 Cite as: Kennefick, M., Maslovat, D., Chua, R., & Carlsen, A. N. (2016). Corticospinal excitability is reduced in a simple reaction time task requiring complex timing. Brain Research, 1642, 319-326. DOI: 10.1016/j.brainres.2016.04.006.
© Copyright 2016 by Dana Maslovat & Anthony N. Carlsen All rights reserved. This article or any portion thereof may not be reproduced or used in any manner whatsoever without the express written permission of the publisher except for the use of brief quotations in a review.
a hybrid of the two (Pacut, 1977). In terms of RT
differences due to movement complexity, response
initiation may be delayed due to either reduced rate of
increase in activation, or a greater amount of required
activation. Furthermore, an increased activation
requirement could be due to either a higher initiation
threshold (Maslovat et al., 2011), or activation beginning
from a lower state (or level) of preparatory activation at
the time of the imperative signal (Carlsen et al., 2012;
Maslovat et al., 2014).
Although response complexity effects have been
considered within a neural activation context, few studies
have directly assessed cortical activation associated with
various movement complexities, and results have been
mixed. For example, Kitamura and colleagues (1993) found
no activation differences during simple and complex
sequential finger movements using
electroencephalography, while Shibasaki and colleagues
(1993) showed differences in motor cortical cerebral blood
blow between simple and complex sequential finger
movements through the use of positron emission
tomography. The effect of response complexity on
corticospinal excitability (CE) has also been examined using
transcranial magnetic stimulation (TMS) during static as
well as continuous motor tasks, although not in the context
of a RT paradigm. TMS applied over primary motor cortex
can evoke a short latency excitatory response in a targeted
muscle (motor evoked potential, MEP), and activates
corticospinal neurons both directly and indirectly through
cortico-cortical synapses (Taylor, 2006). Flament and
colleagues (1993) compared CE levels between a simple
static finger abduction and a variety of more complex static
gripping tasks and showed that MEPs were larger in the
complex tasks compared to those in the simple finger
abduction task. Similarly, Abbruzzese and colleagues (1996)
found increased MEP amplitudes for more complex
movements during both the production of, or mental
simulation of continuous repetitive and sequential finger
movements (see also Roosink and Zijdewind, 2010).
The effects of response complexity on CE in a RT
paradigm were recently examined by Greenhouse et al.
(2015), who used TMS to assess transient motor inhibition
during the response preparation phase of a movement in
both a simple and choice RT paradigm. The authors varied
the complexity of these movements by increasing either
the number of muscles or number of elements involved in
performing a movement. When the number of muscles
involved increased, there was no corresponding increase in
RT; however, CE was suppressed for the more complex
response. Conversely when the number of movement
elements was increased, both RT and CE increased for the
more complex movement. While this provides evidence
that motor system excitability during movement
preparation is sensitive to response complexity, it is unclear
why an increase in CE would be associated with longer RT
for the sequenced movements. This result appears to be in
contrast to the predictions of neural activation models,
which predict longer RTs for complex movements related
to lower levels of activation with respect to an initiation
threshold.
The evidence above suggests that response complexity
can affect neural activation levels; yet the relationship
between CE and response latency as a function of
complexity of the required movement is still unclear.
Therefore, the purpose of the current study was to
investigate how response complexity affects CE in a simple
RT paradigm. Participants performed simple RT tasks
requiring either a single key press or a three key press
sequence with a non-isochronous timing structure, as this
has shown to be a robust method to manipulate response
complexity and thus increase simple RT (Maslovat et al.,
2014). TMS was used to probe CE in 25 ms intervals
between 0 and 125 ms following the go-signal (i.e., during
the RT interval) in order to quantify changes in the time
course of excitability during the response initiation phase,
rather than assessing excitability during the preparation
phase (e.g., Greenhouse et al., 2015). It was expected that
the more complex movement would result in longer simple
RTs, and that CE would increase prior to the onset of both
simple and complex movements. However, of greater
interest was a comparison between activation curves for
the two movements between the go-signal and response
onset. Based on neural activation models (Carlsen et al.,
Full Publication Information: http://dx.doi.org/10.1016/j.brainres.2016.04.006 Cite as: Kennefick, M., Maslovat, D., Chua, R., & Carlsen, A. N. (2016). Corticospinal excitability is reduced in a simple reaction time task requiring complex timing. Brain Research, 1642, 319-326. DOI: 10.1016/j.brainres.2016.04.006.
© Copyright 2016 by Dana Maslovat & Anthony N. Carlsen All rights reserved. This article or any portion thereof may not be reproduced or used in any manner whatsoever without the express written permission of the publisher except for the use of brief quotations in a review.
2012; Maslovat et al., 2014), it was hypothesized that if the
MEP amplitude was lower at presentation of the
imperative stimulus (IS) the longer RTs observed for more
complex movements could be attributed to a lower overall
preparatory level. In contrast, if preparatory MEPs were
not different between tasks, longer RTs observed in a more
complex task may be attributed to either differences in
activation onset latencies or accumulation rates -
evidenced by either a later increase from baseline MEP or
activation increase occurring at slower rate following the IS.
2. Results
2.1 Voluntary response measures
In order to determine if the complexity manipulation
led to differences in RT and/or EMG characteristics,
response output measures for the simple and complex
movements were compared at the baseline time point (i.e.,
TMS stimulation at the IS - see 4.7 for details). Analysis of
mean premotor RT (Figure 1A) confirmed that RT in the
complex task was significantly longer (T(15) = 4.24, p <
.001, r = .74) than in the simple task, similar to what has
been shown previously (Maslovat et al., 2014). Analysis of
peak EMG between simple and complex conditions (Figure
1B) revealed that peak EMG was significantly greater (T(15)
= 3.25, p = .005, r = .64) in the simple compared to the
complex movement. Similarly, the simple movement had a
significantly larger (T(15) = 3.06, p = .008, r = .62)
integrated EMG over the entire burst (iEMG) as compared
to the more complex movement (Figure 1C). Finally,
analysis of integrated muscle activation in the rising phase
(first 30 ms) of the EMG burst (Q30) also revealed that the
early rate of increase in the simple movement was
significantly greater (T(15) = 5.57, p < .001, r = .82) than
that of the complex movement (Figure 1D).
Figure 1. Boxplots of voluntary response measures for the simple and the
complex tasks. Box boundaries represent between-participant first and
third quartiles, solid horizontal lines represent medians, the small square
inside the box plots represents mean, and error bars represent the farthest
outliers within 1.5 times the inter-quartile range from the box boundaries.
Horizontal dashed lines represent within-participant 95% confidence
intervals from the mean. A) Premotor reaction time (RT); B) Peak value of
rectified and filtered EMG from first voluntary agonist burst; C) Integrated
EMG (iEMG) from full duration of raw rectified first voluntary agonist EMG
burst; D) Integrated EMG from the first 30 ms of raw rectified voluntary
activity in first agonist burst. Asterisks (*) denote a significant difference
between the simple and complex movements.
Full Publication Information: http://dx.doi.org/10.1016/j.brainres.2016.04.006 Cite as: Kennefick, M., Maslovat, D., Chua, R., & Carlsen, A. N. (2016). Corticospinal excitability is reduced in a simple reaction time task requiring complex timing. Brain Research, 1642, 319-326. DOI: 10.1016/j.brainres.2016.04.006.
© Copyright 2016 by Dana Maslovat & Anthony N. Carlsen All rights reserved. This article or any portion thereof may not be reproduced or used in any manner whatsoever without the express written permission of the publisher except for the use of brief quotations in a review.
2.2 MEP measures
Representative individual EMG traces from a single
participant at each analyzed stimulation time point (0 – 75
ms, see 4.7), for both simple and complex movement tasks
are shown in Figure 2. Mean MEP amplitudes for the
stimulation time points 0 to 75 ms following the IS are
shown in Figure 3. Although there was no significant main
effect for task (F(1,15) = 0.890, p = .361, ηp2 = .056), there
was a significant main effect for time (F(3,45) = 20.346, p <
.001, ηp2 = .576) indicating that MEP amplitudes increased
along with time following the go-signal. Post-hoc tests
analyzing differences in MEP amplitude between baseline
(0 ms) and subsequent time points (collapsed across
movement type) indicated that there were no significant
differences between the 0 ms and 25 ms time point (p =
.319), but MEP amplitude increased significantly compared
to all previous time points for the 50 ms and 75 ms TMS
stimulation times (all t ratios > 3.36, all corrected p values <
.026).
There was no significant Task x Time interaction for
MEP amplitude with respect to the IS, although the result
approached conventional levels of significance (F(3,45) =
2.519, p = .070, ηp2 = .144). Thus in order to directly test the
hypothesis that CE would be lower for the complex task at
the time of the go-signal, peak-to-peak MEP amplitudes
measured at baseline (IS onset, 0 ms) were analyzed
separately. No difference was observed (T(15) = 0.09, p =
.927, r = .02) in MEP amplitude between the simple (M =
0.389 mV, SD = 0.27) and the complex (M = 0.388 mV, SD =
0.27) movements (see Figure 3, time 0).
Normalized MEP amplitudes in time bins prior to EMG
onset are shown in Figure 4. Analysis at each time bin
confirmed a significant difference between the simple and
the complex condition only at 75 ms prior to EMG onset (U
= 8553, z = -2.62, p = .009, r = -.154) with all other p values
> .35.
Figure 2. Representative EMG traces for the time period of -100
ms to +300 ms with respect to the go-signal (0 ms). The first 300
ms of individual trials are shown from a single subject in both the
simple (black) and complex (grey) tasks, for TMS stimulation time
points 0, 25, 50 and 75ms following the imperative go-signal. Go-
signal is shown as dashed line, and TMS pulse as short vertical bar
in each trace. Motor evoked potential (MEP) measurement
windows are highlighted with a grey area for each trial, and time
of voluntary EMG onset (premotor RT) is indicated in each trial
with a black arrow.
Full Publication Information: http://dx.doi.org/10.1016/j.brainres.2016.04.006 Cite as: Kennefick, M., Maslovat, D., Chua, R., & Carlsen, A. N. (2016). Corticospinal excitability is reduced in a simple reaction time task requiring complex timing. Brain Research, 1642, 319-326. DOI: 10.1016/j.brainres.2016.04.006.
© Copyright 2016 by Dana Maslovat & Anthony N. Carlsen All rights reserved. This article or any portion thereof may not be reproduced or used in any manner whatsoever without the express written permission of the publisher except for the use of brief quotations in a review.
Figure 3. Mean (± within participant 95% CI) MEP amplitudes at TMS
delivery times following the imperative go-signal for both the simple
(black) and the complex (grey) tasks. Note that at time zero the means are
very similar, and the 95% confidence intervals fully overlap. Asterisks (*)
denote a significant difference between presentation times (collapsed
across task).
Figure 4. Boxplot showing MEP amplitudes for both the simple (black)
and the complex (grey) tasks as a percentage of baseline and grouped into
time bins relative to EMG onset (numbers in each box denote how many
observations contribute to each distribution). Box boundaries represent
inter-quartile range, horizontal lines show medians, and small squares
show means. Error bars represent one standard deviation from the mean,
and horizontal dashed lines represent 95% confidence intervals from the
mean. An asterisk (*) denotes a significant difference in MEP amplitude
between the tasks at 75 ms prior to EMG onset. Thin lines are shown
connecting mean values for each condition (Note: connected means,
shown as filled squares, are offset from center of boxes for visual
alignment).
3. Discussion
The purpose of this study was to examine the
relationship between simple RT and the excitability of the
motor pathways prior to initiation of movements, as a
function of differing levels of complexity. Previous work has
shown that RT for a complex task is typically longer than
that for a simple task, a result that has been attributed to
additional programming (Henry and Rogers, 1960),
sequencing requirements (Klapp, 1995), or timing
preparation (Maslovat et al., 2014). The results of the
current study show that task complexity was successfully
manipulated within a simple RT paradigm (confirmed by a
significantly longer RT following the more complex task,
Figure 1A), allowing a novel comparison of CE between the
two movement tasks during the RT interval. Even though
there were no differences in the initial preparatory
activation state between the two movement tasks (i.e., at
the IS), neural activation levels increased in both tasks
following the go-signal (i.e., during the RT interval).
Although the change in CE with time following the IS was
not significantly different between the tasks (Figure 3), a
lower level of excitability was apparent for the complex
task when the data were examined with respect to EMG
onset (Figure 4).
Although a lower level of neural activation for a more
complex movement may initially seem counter-intuitive,
these results are consistent with neural activation models
that suggest that RT differences may be in part related to
cortical activation level prior to response output - although
these models had yet to be tested for movements involving
different complexities. Within the context of a neural
activation framework, several possible explanations may
account for the observed delayed response initiation that
accompanies more complex movements. For example, a
longer RT could be the result of a lower level of preparatory
activation (Carlsen et al., 2012; Maslovat et al., 2014), a
higher initiation threshold (Maslovat et al., 2011; Nazir and
Jacobs, 1991), a decreased rate of activation accumulation
(Carpenter and Williams, 1995; Hanes and Schall, 1996), or
some combination of these.
Full Publication Information: http://dx.doi.org/10.1016/j.brainres.2016.04.006 Cite as: Kennefick, M., Maslovat, D., Chua, R., & Carlsen, A. N. (2016). Corticospinal excitability is reduced in a simple reaction time task requiring complex timing. Brain Research, 1642, 319-326. DOI: 10.1016/j.brainres.2016.04.006.
© Copyright 2016 by Dana Maslovat & Anthony N. Carlsen All rights reserved. This article or any portion thereof may not be reproduced or used in any manner whatsoever without the express written permission of the publisher except for the use of brief quotations in a review.
In the current study, mean raw MEP amplitude data
indicated that CE measured at the IS was not different
between the two movements (p = .927), signifying that
initial cortico-spinal preparatory activation level was not
affected by differing response complexity. This contrasts
with previous studies that have shown that CE is increased
for movements of greater complexity (Abbruzzese et al.,
1996; Flament et al., 1993), although these were not
conducted within the context of a RT framework. Those
studies showing an increase in CE with response complexity
have used tasks which required a greater degree of motor
unit recruitment such as simple finger abduction versus
gripping (Flament et al., 1993). As such, during more
complex ongoing static tasks, increased CE may simply be
related to the number of muscles and/or motor units
involved in the action. The current study manipulated
complexity in a qualitatively different way by requiring
additional movement elements from the same effector.
Because the preparatory CE was not different between
levels of complexity, this suggests that the preparatory CE
may be primarily determined by the task requirements of
the first element in a movement sequence.
Similarly, examining the normalized MEP data time-
locked to EMG onset (Figure 4) indicated that threshold
levels were not higher for the complex movement, as CE
was lower in the complex task as compared to the simple
task just prior to response output. This is in contrast to a
recent study that provided evidence that increasing the
number of movement elements led to a marginally reliable
increase in MEP amplitudes (p = .06) (Greenhouse et al.,
2015). However, important differences in methods
between the two studies may have contributed to this
discrepancy. First, the study by Greenhouse et al. (2015)
examined CE during the RT foreperiod (i.e. preparatory
phase), whereas in the current study the time course of CE
was examined during the RT interval (i.e. initiation phase).
Secondly, the sequenced movement used by Greenhouse
et al. (2015) required the use of multiple effectors with no
specific timing requirement. Conversely, in the current
study increased complexity was achieved by requiring
multiple button presses of a single key with an imposed
timing structure, using the same effector.
While the present data indicate that the change in CE
following the go-signal was not different between the tasks
(Figure 3), it is prudent to note that a marginal interaction
effect (p = .070) was found between the tasks and TMS
delivery points. This interaction hints at a slower rate of
increase in CE for the complex compared to the simple
movement following the IS (Figure 3). Although speculative,
the data in Figure 3 suggest that CE may have begun to
increase above baseline at a later time point for the
complex movement, although the relatively large 25 ms
time bins make it difficult to identify the precise point of
increase from baseline and loss of short RTs for the later
TMS stimulation points may contribute to this finding. On
the other hand, because RTs were approximately 20 ms
longer in the complex condition, the rise in CE observed in
Figure 4 would have been delayed on average by ~20 ms.
While a delayed increase in neural activation for the
complex movement may partially contribute to the longer
RT value, when data were aligned to EMG onset, it is clear
that the amount of excitability increase is significantly
lower (p = .009) for the complex movement in the final
time bin (< 75 ms) preceding movement initiation (Figure
4), suggesting a possible lower rate of increase in
excitability for more complex movements.
Although the current data provide novel evidence that
the lengthened RT for a complex movement is
accompanied by a reduction in CE, these results cannot in
isolation identify the site(s) responsible for a change in
MEP amplitude, which has previously been shown to
depend on the excitability of both cortical and spinal
neurons (Taylor, 2006). It is also worth noting that the
reduction in CE observed leading up to voluntary response
onset in the complex task was also reflected in the
voluntary response outcome measures. Specifically, while a
lowered level of activation for the sequenced movement
during the RT interval was associated with longer RT (Figure
1A), the reduced CE also led to a less forceful response for
the complex task, as evidenced by reduced peak EMG
amplitude (Figure 1B), as well as a reduced overall
integrated EMG area for the muscle burst (Figure 1C), and a
reduced rate of rise of the initial EMG activation (Figure
1D). As such, it is worth considering why a more complex
Full Publication Information: http://dx.doi.org/10.1016/j.brainres.2016.04.006 Cite as: Kennefick, M., Maslovat, D., Chua, R., & Carlsen, A. N. (2016). Corticospinal excitability is reduced in a simple reaction time task requiring complex timing. Brain Research, 1642, 319-326. DOI: 10.1016/j.brainres.2016.04.006.
© Copyright 2016 by Dana Maslovat & Anthony N. Carlsen All rights reserved. This article or any portion thereof may not be reproduced or used in any manner whatsoever without the express written permission of the publisher except for the use of brief quotations in a review.
movement resulted in a differentially lower CE compared
to a more simple task, as the current data cannot
distinguish between whether decreased CE led to increased
RT and a diminished voluntary response output, or whether
a less forceful planned response is responsible for the
diminished CE and hence, increased RT. That is, while there
does appear to be a correlation between activation levels
and response output measures, it is not possible to
determine the direction of causality. One possibility for the
diminished CE is that additional inhibitory mechanisms are
involved in the production of a sequenced movement.
Because the complex movement involved a specific and
complex timing structure, cerebellar input may be
responsible for this inhibition, resulting in longer RT and
diminished response output measures. The cerebellum has
long been considered to play a major role in the planning,
initiation and organization of timed movement (Allen and
Tsukahara, 1974) with the olivocerebellar system identified
as a unique timing control system that has strong inhibitory
connections to the motor cortex (see Llinas, 2014 for a
recent review); however, testing this possibility would
require further investigation. While increased inhibition is
one explanation for the lowered MEP amplitudes for the
complex task, it is also possible that a shift rather than
reduction in activation is responsible for our observed
results. That is, it may be the case that the reduced
forcefulness of response (as evidenced by the decreased
EMG activity for the more complex movement) resulted in
less activation required leading up to response execution.
In conclusion, the findings of the current study indicate
that increasing movement complexity by adding additional
elements with a specific timing requirement results in
reduced CE during the RT interval, but only in the final 75
ms leading up to response production. The observed
slower RT and reduced EMG output in the complex task
therefore appear to be related to a reduction in CE,
providing a novel correlate to previously reported response
complexity effects.
4. Experimental Procedure
4.1 Ethical approval
Fully informed, written consent was obtained from all
participants prior to the study. The study was conducted in
accordance with ethical guidelines approved by the
University of Ottawa’s Research Ethics Board (REB
approval: H03-12-03) and conformed to the guidelines of
the Declaration of Helsinki.
4.2 Participants
Sixteen healthy volunteers (11M, 5F; mean age 25 ± 5
years), with normal or corrected–to-normal vision, and
with no history of neurological, sensory, or motor disorders
participated in this study. All participants were classified as
right-handed or ambidextrous participants based on the
Edinburgh Handedness Inventory (Oldfield, 1971). Testing
of each participant took place in a single session, and
required approximately 1.5 hours to complete.
4.3 Experimental set-up and task
Participants sat comfortably facing a 23-inch LCD
computer monitor with their right arm pronated and
resting on a flat surface, and were informed that the
upcoming task was a simple RT task consisting of a button
press movement of a single telegraph key (Ameco AM-K4B)
using only the right index finger. For the simple movement,
the participant was required to press the telegraph key
once for a duration of 150 ms, while the complex
movement required a three key press sequence using only
the right index finger in which the first two presses were
separated by 150 ms and the second and third presses
were separated by 450 ms (individual key press durations
of 150 ms). These movements were chosen as they have
previously been shown to exhibit large simple RT
differences (Maslovat et al., 2014). All trials began with the
word “Ready!” appearing on the screen, followed by a
visual cue in the center of the monitor (simple = “dit”;
complex = “dit dit ___ dit”) and an auditory template of the
movement in which tones (80 dB, 150 ms, 500 Hz)
represented the movement pattern including the amount
Full Publication Information: http://dx.doi.org/10.1016/j.brainres.2016.04.006 Cite as: Kennefick, M., Maslovat, D., Chua, R., & Carlsen, A. N. (2016). Corticospinal excitability is reduced in a simple reaction time task requiring complex timing. Brain Research, 1642, 319-326. DOI: 10.1016/j.brainres.2016.04.006.
© Copyright 2016 by Dana Maslovat & Anthony N. Carlsen All rights reserved. This article or any portion thereof may not be reproduced or used in any manner whatsoever without the express written permission of the publisher except for the use of brief quotations in a review.
of time the telegraph key should be pressed and time
between presses. The visual precue stayed on the screen
for the duration of the foreperiod, which was randomly
selected between 2500-3500 ms, and was followed by an
auditory IS (82 dB, 40 ms, 1000 Hz), at which time the
participant initiated their movement. All auditory tones
were generated using digital to analog hardware (National
Instruments PCI-6024E), with the signal amplified and
presented via a loudspeaker (MG Electronics Model M58-
H) located in front of the participant.
Participants were instructed to initiate the required
movement as quickly as possible in response to the IS while
executing the timing pattern as accurately as possible.
Feedback was provided on the computer monitor after
each trial, consisting of RT and timing accuracy. Accuracy
represented the participant’s ability to replicate the
auditory template played prior to the IS, and consisted of a
visual display of the closing and opening of the telegraph
key displayed beneath a template of the movement. If the
participant incorrectly replicated the auditory template
(defined as greater than 100 ms error on any key press
duration or interval), the on-screen feedback would be red
and the trial was omitted from analysis (total 101 trials, 49
in the simple task, 52 in the complex task; total 3.5% of
trials across participants); otherwise it would appear green
indicating a correct response. A reward structure was
provided to the participant whereby five points were
awarded to the participant when the response feedback
turned green and five points were awarded when
displacement RT was below a predetermined criterion
(which was initially set at 250 ms, but adjusted based on
the participant’s practice performance). These points had
no monetary significance and were simply used as a means
to increase participant motivation to perform accurate
movements initiated at short latency. Each participant
began by completing a practice session consisting of a block
of 10 simple movements followed by a block of 10 complex
movements. Following practice, participants performed
testing trials which were identical to the practice trials,
with the exception that TMS was applied at six time points
following the IS (0 ms, 25 ms, 50 ms, 75 ms, 100 ms, 125
ms). Previous research involving TMS delivery during the RT
interval typically either used a protocol in which TMS is
time-locked to a proportion of individual RT (Tandonnet et
al., 2012) or fixed intervals following the IS (Duque et al.,
2010). The current study time-locked the TMS to the IS as
the primary research question involved the examination of
the relative difference in activation levels between the
movements both at the IS and moving forward in time until
response output (i.e., during the RT interval). Testing
consisted of 180 trials separated into 5 blocks of 36 trials,
including 18 simple and 18 complex movements (i.e., 3
trials of each of the 6 TMS stimulation points for each level
of complexity). The order of the trials within a block was
randomized and controlled by a computer. The task is
visually represented in Figure 5.
Figure 5. Visual representation of the timeline of a testing trial,
including TMS stimulation points which are represented by
downwards pointing arrows.
4.4 Transcranial magnetic stimulation
TMS pulses were applied using a figure-8 magnetic coil
(70mm; Magstim 2002, Magstim Company Ltd, UK). Prior
to testing, the coil was placed over the optimal location for
eliciting MEPs from the right flexor digitorum superficialis
(FDS), with the handle of the coil pointing backwards at a
45˚ angle. The starting location was found by first finding
the midpoint between the nasion and inion, and the left
and right preauricular notches. From this midpoint, a
location 5 cm lateral and 1 cm posterior was marked on the
participant’s scalp using a red grease crayon. The optimal
location was then found by delivering single test pulses at
Full Publication Information: http://dx.doi.org/10.1016/j.brainres.2016.04.006 Cite as: Kennefick, M., Maslovat, D., Chua, R., & Carlsen, A. N. (2016). Corticospinal excitability is reduced in a simple reaction time task requiring complex timing. Brain Research, 1642, 319-326. DOI: 10.1016/j.brainres.2016.04.006.
© Copyright 2016 by Dana Maslovat & Anthony N. Carlsen All rights reserved. This article or any portion thereof may not be reproduced or used in any manner whatsoever without the express written permission of the publisher except for the use of brief quotations in a review.
various scalp locations around this mark and determining
the location that resulted in consistently large MEPs.
Resting motor threshold (RMT) was determined at rest to
the nearest 1% of stimulator output using the Rossini-
Rothwell (Rossini et al., 1999) method (defined as the
minimum intensity required to evoke MEPs above 50 µV in
at least 5 out of 10 trials). The magnetic coil was held
stationary over the optimal location by the experimenter
and the position was maintained by holding the coil in the
reference position on the head with the assistance of
neuronavigation hardware and software (ANT Neuro Visor
2, Madison, WI). During experimental trials, stimulus
intensity was adjusted to 110% of RMT as similar intensities
have been used previously to probe changes in CE (Chen et
al., 1998; MacKinnon and Rothwell, 2000). Across
participants RMT was 47% (SD = 10) of maximal stimulator
output, and the mean test stimulus was 52% (SD = 11) of
maximal stimulator output.
4.5 Recording equipment
Surface electromyography (EMG) data were collected
from the muscle belly of the primary effector muscle, the
right FDS, using a bipolar preamplified (gain = 10) surface
electrode (Delsys Bagnoli DE-2.1) connected via shielded
cabling to an external amplifier (Delsys Bagnoli-8,
bandwidth 20-450 Hz). The electrode was placed parallel to
the muscle fibres, and attached to the skin using double-
sided adhesive strips. A ground electrode (Dermatrode HE-
R) was placed on the participant’s right lateral epicondyle.
The site of the electrode was cleaned using abrasive skin
prepping gel and alcohol wipes. The telegraph key was
connected to a DC power source such that +5V was
produced when the switch was closed (depressed) and 0V
was produced when the button was open. Data collection
for each trial was initiated by the computer 500 ms prior to
the warning signal and continued for 2000 ms. Unfiltered
EMG and telegraph key signals were digitally sampled at
1kHz (National Instruments PCI-6024E) using a custom-
made program written in LabVIEW (National Instruments
Inc.) and stored for offline analysis.
4.6 Dependent Measures
Practice trials were omitted from analysis. Voluntary
EMG onset in the agonist was defined as the first point
(non-MEP related) where the rectified and filtered (25 Hz
low pass elliptical filter) EMG activity first reached a value
of two standard deviations above baseline levels (mean
EMG activity in a 100 ms interval following the warning
signal) and was maintained for a minimum of 20 ms. EMG
onset points were first determined using a custom program
written in LabVIEW (National Instruments Inc.) and then
were visually confirmed and manually adjusted (if
necessary) to compensate for any errors due to the
strictness of the algorithm and to dissociate between
voluntary EMG and MEPs. EMG offset point was
determined in a similar fashion.
Response output measures included premotor RT
(time between the go-signal and the EMG onset), peak
EMG (maximum value obtained between onset and offset),
initial rise of the EMG agonist burst (Q30; integration of
rectified raw EMG for first 30 ms), and size of initial EMG
burst (iEMG; integration of rectified raw EMG for entire
burst duration). Reaction times that were longer than 350
ms (36 trials: 4 simple response, 32 complex response) or
shorter than 50 ms (6 trials: 5 simple response, 1 complex
response) were excluded from the analysis. These were
considered to be bad trials where the participants either
reacted too slowly to have been properly preparing for the
task or anticipated the IS.
MEP amplitude was defined as the largest peak-to-
peak amplitude recorded in a 25 ms window starting 20 ms
after the TMS pulse (to allow for neural conduction). Trials
in which a MEP was not detectable were rejected (often
due to the MEP occurring during the EMG burst), which
resulted in the removal of 25.2% of trials across
participants (435 simple, 291 complex), or 726 total trials (0
ms = 30; 25 ms = 26; 50 ms = 34; 75 ms = 101, 100 ms =
219; 125 ms = 316). This breakdown indicates that the MEP
occurred during the EMG burst much more frequently in
trials with TMS applied at 100 ms and 125 ms following the
IS. As such this led to missing data points for these time
conditions for 5 of the 16 participants and an overall
Full Publication Information: http://dx.doi.org/10.1016/j.brainres.2016.04.006 Cite as: Kennefick, M., Maslovat, D., Chua, R., & Carlsen, A. N. (2016). Corticospinal excitability is reduced in a simple reaction time task requiring complex timing. Brain Research, 1642, 319-326. DOI: 10.1016/j.brainres.2016.04.006.
© Copyright 2016 by Dana Maslovat & Anthony N. Carlsen All rights reserved. This article or any portion thereof may not be reproduced or used in any manner whatsoever without the express written permission of the publisher except for the use of brief quotations in a review.
rejection rate of over 56% of the trials in these conditions.
Additionally, trials in which a MEP was measurable when
TMS was presented at 100 ms or 125 ms following the IS
were necessarily trials with longer RTs, and thus activation
at these time points was less representative of that
occurring in a typical trial. This is evidenced by the mean RT
values being considerably longer for both simple and
complex movements in trials where a measureable MEP
was detected when TMS was delivered at 100 or 125 ms
following the IS (simple M = 208 ms, complex M = 220 ms)
compared to the earlier TMS time points (simple M = 145
ms, complex M = 164 ms). As such, data from these two
time points were discarded from the primary analysis. The
loss of these data points is a potential drawback to time-
locking the TMS delivery to the IS, rather than delivering
TMS based on individual mean RT values (as previously
outlined). Given the variability associated with typical RTs,
TMS delivery time-locked to individualized mean RT values
would also likely have resulted in a relatively large number
of discarded trials. Nevertheless, to compensate for this
limitation in our IS-locked protocol, MEP amplitudes were
analyzed both with respect to the IS and EMG onset such
that activation timelines could be determined following the
IS and prior to movement onset (see section 4.7 below).
Finally, trials were excluded from analysis if root mean
square (RMS) EMG activity in the 100 ms preceding the
TMS pulse in any individual trial exceeded twice the resting
RMS value for that trial (determined from a mean of 100
ms EMG prior to the warning signal); trials that fit this
criterion must have also had a pre-TMS RMS EMG value
greater than 10 microvolts. This procedure resulted in the
exclusion of 56 additional trials (1.9%). Finally, MEP
amplitudes greater than 3 standard deviations from each
individual’s overall mean were removed from the analysis,
which resulted in the removal of an additional 10 trials.
Overall the primary analyses included 1562 of the 1920
total trials when the TMS was presented between 0 to 75
ms following the IS (81% inclusion rate).
4.7 Statistical Analyses
In order to examine the effects of the complexity
manipulation on production of the movement independent
of any effects of late TMS, paired samples Student’s t-tests
were performed for each of the response output measures
(premotor RT, peak EMG, iEMG, and Q30), comparing the
simple versus complex movement at the first TMS delivery
time point. Shapiro-Wilk tests showed that data for peak
EMG, iEMG, and Q30 were all significantly non-normal (p
<.05) and thus were subjected to a Log10 transform prior
to analysis, which corrected for significant violations (all
post transformed p values > .1). Only the data when the
TMS was presented concurrent with the IS was considered
for this analysis as removal of trials where EMG onset
preceded MEP onset were more prevalent for the later
TMS time points which may have led to non-representative
data for these later time points.
Prior to examination of MEP amplitudes, RMS of
background EMG in the 100 ms preceding TMS onset was
collapsed across TMS delivery times and compared
between complexity conditions using a single paired
samples Student’s t-test. This analysis confirmed that there
was no significant difference in background EMG between
conditions (T(15) = 0.133, p = .896, r = .03).
MEP amplitudes were subjected to two separate
analyses in order to accurately describe the time course of
CE for the simple and complex movement with respect to
both the IS and EMG onset. Shapiro-Wilk tests showed that
raw MEP data were significantly non-normal (p <.05) and
thus were subjected to a Log10 transform prior to the first
analysis, which corrected for significant violations (all post-
transformed p values > .14). First, to investigate any
changes in activation following the IS, raw MEP amplitudes
were analyzed using a 2 Task (simple, complex) x 4 Time (0
ms, 25 ms, 50 ms, 75 ms) repeated measures ANOVA.
While the analysis above captures activation changes
following the IS, it does not provide comparable
information relative to movement onset as RT differences
were expected between the simple and complex
movement. Thus, a second analysis investigated MEP
amplitude data time-locked to the onset of EMG by
Full Publication Information: http://dx.doi.org/10.1016/j.brainres.2016.04.006 Cite as: Kennefick, M., Maslovat, D., Chua, R., & Carlsen, A. N. (2016). Corticospinal excitability is reduced in a simple reaction time task requiring complex timing. Brain Research, 1642, 319-326. DOI: 10.1016/j.brainres.2016.04.006.
© Copyright 2016 by Dana Maslovat & Anthony N. Carlsen All rights reserved. This article or any portion thereof may not be reproduced or used in any manner whatsoever without the express written permission of the publisher except for the use of brief quotations in a review.
calculating the time difference between the MEP and the
onset of EMG. These data were organized into time bins in
which MEP onsets occurred either <75 ms prior to EMG
onset or in 25 ms time bins at increasing intervals up to
>150 ms prior to EMG onset (see Chen et al., 1998 for a
similar analysis). Note that for this analysis, trials from all
TMS delivery times where a MEP was noted were used
(including 100 ms and 125 ms); error trials, trials with RTs
outside of 50-350 ms, and trials with excessive RMS activity
preceding the TMS were excluded (see above). Thus this
analysis included a total of 1910 of 2880 trials (66.3%
inclusion rate). Because not all participants had data values
for all time bins, each trial was considered as an individual
observation resulting in what can be considered between-
group analysis. As such, in order to compensate for inter-
individual variability in MEP amplitudes, raw peak-to-peak
MEP values were normalized for each participant by
expressing them as a percentage of their own mean MEP
amplitude at time 0 (i.e. baseline, 100%) in both the simple
and complex tasks. The resultant distributions were
analyzed for normality using Shapiro-Wilk tests revealing
that MEP distributions all bins were significantly non-
normal (all p values < .002). Transforming the data led to
no improvement in normality, thus untransformed binned
MEP amplitudes were analyzed separately using Mann-
Whitney U tests for rank ordered data between the simple
and complex conditions at each time bin (Bonferroni-
corrected for multiple comparisons). Note that the MEP
normalization procedure employed is different to previous
research examining the time course of CE, which have
often used time points prior to the IS as a baseline measure
(Duque et al., 2010; Tandonnet et al., 2012; Touge et al.,
1998). Although these studies have shown a reduction in
CE at the IS as compared to the warning period, the current
study was primarily interested in a comparison of CE
timelines between task complexities from the IS until
response output, and thus the IS time point was used as a
baseline indicator.
For repeated measures ANOVAs, the Greenhouse-
Geisser Epsilon factor was used to adjust the degrees of
freedom for violations of sphericity if necessary.
Uncorrected degrees of freedom are reported, with the
corrected p-values and partial eta squared (ηp2) and r
values reported as measures of effect size. Post-Hoc tests
were performed using Bonferroni-corrected paired samples
Student’s t-tests where appropriate. Untransformed
means, standard deviations, and within-participant
confidence intervals (see Cousineau, 2005; Morey, 2008)
are reported and/or presented in figures where null
hypothesis significance tests were performed on
transformed variables. Differences with a probability of less
than .05 were considered significant.
Grants
This research was supported by a Natural Sciences and
Engineering Research Council of Canada (NSERC) Discovery
Grant (RGPIN 418361-2012) awarded to Anthony N.
Carlsen.
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